Computational Drug Repurposing Algorithm Targeting TRPA1 Calcium Channel as a Potential Therapeutic Solution for...

Area of Science:

• Neuroscience
• Pharmacology
• Computational Chemistry

Background:

• Multiple sclerosis (MS) is a chronic CNS autoimmune disease causing neurodegeneration and demyelination.
• The TRPA1 calcium channel is a potential therapeutic target in MS, with inhibition showing neuroprotective effects.

Purpose of the Study:

• To identify repurposable drugs as potent TRPA1 antagonists for potential multiple sclerosis treatment.
• To leverage computational drug discovery and data mining for identifying novel therapeutic agents.

Main Methods:

• In silico screening combining chemical graph mining, QSAR modeling, and molecular docking.
• Screening of the DrugBank database to identify potential TRPA1 inhibitors.
• Evaluation of drug candidates for inhibition probability, pharmacokinetics, and blood-brain barrier permeability.

Main Results:

• 903 repurposable structures were initially selected from the DrugBank database.
• 97 compounds demonstrated satisfactory inhibition probabilities and pharmacokinetic profiles.
• Desvenlafaxine, paliperidone, and febuxostat were identified as top candidates with good BBB permeability and likely allosteric TRPA1 inhibition.

Conclusions:

• Desvenlafaxine, paliperidone, and febuxostat are promising candidates for repurposing as MS therapeutics targeting TRPA1.
• Further in vitro and in vivo studies are warranted to validate the efficacy of these identified compounds.